Face recognition method integrating kernel and Bayesian compressed sensing

Abstract

The invention discloses a face recognition method integrating a kernel and Bayesian compressed sensing. The face recognition method comprises a face recognition system and is characterized by including performing local binary pattern feature extraction, kernel space mapping and Bayesian compressed sensing classification. According to the arrangement, advantages of the compressed sensing plan and the Bayesian method are integrated; according to the compressed sensing plan, original images can be reconstructed by solving a sparse coefficient matrix, by the aid of limiting of prior information of the Bayesian method to the sparse coefficient matrix, influence of noise is avoided to a certain extent, error range is estimated, and the images are reconstructed effectively; influence of factors including light, shielding objects and expression changes to face recognition is overcome, and recognition rate is increased to 99% of the highest; reconstruction recognition is achieved by means of sparse coefficient matrix, and running speed is higher than that of a support vector machine.

Description

Technical field [0001] The invention involves the invention involving machine vision and image processing technology, especially the face recognition system and method. Background technique [0002] In the existing face recognition system, there are many ways to recognize face recognition, such as supporting vector machines, etc., low recognition rates, and cannot overcome changes in face light, expression, cover and other changes. Invention content [0003] The purpose of the present invention is to provide a face recognition method based on the changes in the face -based Bayes compressed perception such as the change of light, expression, and obstruction. [0004] In order to solve the above problems, combined with the idea of compressed perception of nuclear and Bayesia, a new method of face recognition method was designed. First, use a local two -value mode to extract the image features, and then use the cross -cedu nuclear projection of the square diagram to the Gaowite Sym...

AI Technical Summary

Problems solved by technology

[0002] In the existing face recognition system, there are many methods of face recognition, such as support vector machine, etc., the recognition rate is low, and it cannot well overcome changes in face illumination, expression, occlusion, etc.

Images